My paper from the 2011 Atlantic Schools of Business conference: Innovation is a key mechanism for improving economic productivity. The literature suggests approaches to innovation are socially embedded, and protean industrial cultures outperform autarkic ones. This study reports on differences in innovation culture across Canada’s provincial ICT industries, and the impact of those differences on employment growth and decline.

1. ASB 2011 Ryan MacNeil
Charlottetown, Prince Edward Island Department of Business & Tourism
Mount Saint Vincent University
REGIONAL DIFFERENCES IN INNOVATION AND ECONOMIC PERFORMANCE
IN CANADA’S INFORMATION TECHNOLOGY INDUSTRIES1
Innovation is a key mechanism for improving
economic productivity. The literature suggests
approaches to innovation are socially embedded,
and protean industrial cultures outperform
autarkic ones. This study reports on differences
in innovation culture across Canada‟s provincial
ICT industries, and the impact of those
differences on employment growth and decline.
Innovation and Economic Performance
Neoclassical Economic Theory
Government policy in Canada is often informed by neoclassical economic theory. As the theory
goes, regional output of a commodity (Q) is a function of the capital (k) and labour (L) employed
in its production (see Equation 1). By modifying this function, it can be shown that an increase in
productivity (defined as output per unit of labour) is the result of an increase in the ratio of capital
to labour (see Equation 2). Therefore, increases in productivity can only be achieved two ways:
labour must remain constant while capital increases, or capital must increase faster than labour.
Unfortunately, this simplistic version of the theory suggests that technological progress has no
qualitative effect on productivity. Technology can only manifest as additional capital inputs and
reduced labour inputs.
Q = f (k, L) (1)
Q / L = f (k / L) (2)
1
The author wishes to acknowledge Peter V. Hall, Simon Fraser University, for valuable feedback on an
earlier approach to this topic.

2. Endogenous Growth Theory
Acs and Varga (2002, p. 137) compare neo-classical and endogenous growth theories and explain
that the latter allows for “the modeling of technological change as a result of profit-motivated
investments in knowledge creation by private economic agents.” They argue that neo-classical
theory is limited by its assumption of perfect competition and constant returns to scale. In fact,
technology is not a purely „public good‟ since knowledge can be “sticky” (Bourgeois and
LeBlanc, 2002) in time and space. Patents and tacit knowledge can create disparity in
technological diffusion. Firms and regions that can develop “sticky” innovations gain market
power and fixed-term monopoly profits (Bourgeois and LeBlanc, 2002).
Endogenous growth theory attributes productivity growth beyond a change in the capital-labour
ratio to “innovations”. These take the form of product or service innovations, process innovations,
and/or organizational innovations (Morgan, 1997; Bourgeois and LeBlanc, 2002; and Betts,
1998). Product or service innovations can be incremental changes to existing products or services,
or entirely new ones. Process innovations can either reduce the costs or improve the quality of
production (for example, just-in-time inventory systems). Organizational innovations involve
some form of structural advantage, such as the way Walmart coordinates its distribution chain
through computerized inventory systems. Morgan (1997) credits Marx and Schumpeter for
introducing the idea that innovation is the root of regional development in capitalist economies.
Schumpeter‟s seminal work (1943) on innovation and capitalism argues that economic growth
requires innovation. Even when experiencing equal capital and labour growth, the theory suggests
that „innovating firms‟ will see growth in output over those which do not innovate. This
revelation has encouraged governments to divert some resources from expensive capital-
mobilization strategies to innovation-catalyzing ones. However, encouraging innovation defies
simple government intervention.
Not Simply Research and Development
A typical government initiative might involve encouraging research and development. When
discussing the downfalls of typical job-creation strategies for declining regions, Hall (1984)
suggests using an existing or “deliberately implanted” research and development tradition to
create an entrepreneurial tradition. He is cautious, and notes, “such bold strategies may succeed,
but they are likely to take a long time to produce substantial results…no single strategy, but rather
a combination of different approaches, will be appropriate” (p. 35). Despite this hesitation, and
the tradition of peer-juried awarding of university research grants, Hall concludes with a call for
“the establishment of regional quotas to the Research Councils” (in the UK, USA and Canada).
Indeed, there is evidence that the Canadian government‟s university research grants neglect
disadvantaged regions. Over its first five years, the Canada Foundation for Innovation invested
only 3.2% of its total contributions in Atlantic Canada (Beaudin and Breau, 2001, p. 133). But
only measuring innovation in terms of gross expenditures on research and development (GERD)
is inappropriate. GERD is “meant to reflect the degree of innovative effort and intent, not

3. necessarily innovative potential and success” (Bourgeois and LeBlanc, 2002, p. 170). Despite a
low level of government R&D funding grants, Bourgeois and LeBlanc found that Atlantic
Canadian firms in knowledge intensive industries (computer services, engineering consultant
services, and other scientific and computer services) have innovation rates near the national
average (2002, p. 71). However, this innovation is much less likely to involve the introduction of
new capital-intensive technologies than elsewhere in Canada because financial capital is lacking.
They say that, “studies in the last ten years are increasingly rejecting R&D as a master key that
unlocks a linear innovation process, seeing it instead as one of several pieces to the innovation
puzzle” (p. 170).
There is a myth that innovation is unique to technology industries and only happens in R&D
laboratories. Bourgeois and LeBlanc, as well as Beaudin and Breau, note the importance of
innovation to firms in the primary and service sectors. For example, in the Atlantic fish
processing sector between 1988 and 1996, the number of labour-hours declined 40% but the
value-added per hour rose 35% (Beaudin and Breau, 2001, p. 89). These industries “acquire ideas
not from in-house R&D but by tapping into the knowledge and ingenuity of their workers,
suppliers and customers – by networking with research institutions, universities, competitors,
governments, and other stakeholders” (Bourgeois and LeBlanc, 2002, p. 18). Maskell and
Malmberg (1999, p. 21) argue that knowledge-based competition is forcing firms to place “a new
premium on establishing cooperative relations with firms and institutions with complementary
competencies.”
There is a burgeoning volume of research on the social-embeddedness of innovation. Noted
academics argue that community networks encourage the free-flow of ideas and therefore foster
continuous innovation. Morgan (1997, p. 493) says that, “innovation is shaped by a variety of
institutional routines and social conventions.” The Danish Aalborg group of economists goes so
far as to say that “knowledge is the most strategic resource and learning the most important
process” (Ibid.) for regional development. This connects with research on Japanese organizational
innovations that recognizes tacit knowledge as highly personal and difficult to measure. Nelson
(1993) is recognized as the pioneer of research on national innovation systems. 2 He attributes the
rise of Japanese leadership in automotive and consumer electronics production in part to interfirm
linkages (Nelson, 1999, p. 5). Japan is renowned for unique supplier-customer partnership chains
at the interfirm level. At the national level, Japan also has strong interfirm institutions (like trade
and professional associations). Meanwhile, at the intrafirm level, the Japanese kaizen3 approach
results in horizontal information flows and decentralized learning. Storper (1992, 1994, 1995) is
credited with relating these issues of learning, innovation and institutions to the study of
economic geography. His work outlines the importance of untraded interdependencies in
organizational learning.
Feldman and Florida (1994, p. 211) conclude that a broad case study literature, “encourages
scholars to shift focus from the firm-level to a consideration of innovation as a social process.”
They argue that innovation stems from an agglomeration of social and economic institutions
2
Note that Nelson does not consider geography to be as important to innovation as the other authors
referenced here. Nelson (1999, p. 8) says, “it is the connections, not geographic proximity at all…”.
3
“…continuous improvement through interactive learning and problem-solving…” (Morgan, 1997, p. 494)

4. which form part of a broader social structure (Ibid., p. 220). Saxenian‟s work contrasting
Massachusetts‟ „Route 128‟ and California‟s „Silicon Valley‟ supports a similar view. She
describes the innovation in these two regions as „ecosystems‟,
Silicon Valley is like the rainforest. It‟s a
decentralized system with a complex and
continually diversifying mix of species, flora
and fauna that spontaneously and repeatedly
cross-polinate. Route 128, by contrast, using this
metaphor is like a plantation. It‟s a more
centralized system dominated by large
corporations that crowd out local opportunities
for new growth (Saxenian, 1998, p. 3).
Saxenian is critical of science parks and other strategies that aim to create replica Silicon Valleys.
She concludes that, “ultimately regions are best served by policies that help companies to learn
and respond quickly to changing conditions – rather than policies that either protect or isolate
them from competition or external change” (1994, p. 166).
In her work, Saxenian contends that the mechanism of Silicon Valley‟s success was its
collaborative industrial structure. In contrast, she says that Route 128, “came to be dominated by
a small number of large, vertically integrated minicomputer firms…that had minimal
relationships with each other or with local or regional institutions” (Saxenian, 1998, p. 2). If
Saxenian is correct, regions with protean industrial structures (like the versatile, horizontally
networked system in Silicon Valley) will see greater economic growth and resilience than regions
with autarkic structures (like the closed, vertically integrated industrial system of Route 128). The
key difference between these regions would be their approach to innovation. The most successful
regions would be home to firms that collaborate with suppliers, customers, universities and
competitors. The least successful regions would be home to highly secretive firms that make full
use of the law to protect their intellectual property, and of „vertical integration‟ (mergers and
acquisitions) to acquire (rather than create) protected intellectual property.
Method
Approach
This paper presents empirical evidence to support these theories in the Canadian context. It
examines inter-provincial variations in the approach to innovation taken by the information and
communication technology (ICT) service industry. The research question is whether these
variations in innovation culture explain variations in regional economic performance. Maskell

5. and Malmberg (1999, p. 21) proposed this line of inquiry when they asked, “Do firms from
different regions exhibit different patterns of interaction and cooperation?”
Data Sources
The two data sources used in this study were supplied by Statistics Canada and accessed through
the CANSIM database. Provincial employment trends were extracted from the Survey of
Employment, Earnings and Hours (Statistics Canada, 2011). This survey‟s population includes all
business in Canada found on either Statistics Canada‟s Business Register or in Revenue Canada‟s
Business Number Database. From this dataset, provincial employment levels in January 2001 and
January 2011 were extracted for all NAICS 2002 (North American Industrial Classification
System) codes relating to the international standard information and communication technology
(ICT) service industries. Table 1 provides the list of NAICS categories making up the ICT service
industry. Total industry employment and total overall employment were calculated for each
province.
Table 1: Information and Communication Technology Industries by NAICS 2002
NAICS Description
4173 Computer and Communications Equipment and Supplier Wholesaler-Distributors
41791a Office and Store Machinery and Equipment Wholesaler-Distributors
5112 Software Publishers
5171 Wired Telecommunications Carriers
5172 Wireless Telecommunications Carriers (except Satellite)
5173 Telecommunications Resellers
5174 Satellite Telecommunications
5175 Cable and Other Program Distribution
5179 Other Telecommunications
518111b Internet Service Providers
518112b Web Search Portals
5182 Data Processing, Hosting, and Related Services
53242c Office Machinery and Equipment Rental and Leasing
5415 Computer Systems Design and Related Services
8112 Electronic and Precision Equipment Repair and Maintenance
Table Source: Statistics Canada, Survey of Innovation 2003, Methodology Note (p. 3).
a
This classification is unavailable in CANSIM Table 281-0023. The higher level of
classification, “4179 - Other machinery, equipment and supplies wholesaler-distributors” is
used.
b
CANSIM Table 281-0023 combines these two classifications into “5181 - Internet service
providers, web search portals”.
c This classification is unavailable in CANSIM Table 281-0023. The higher level of
classification, “5324 - Commercial and industrial machinery and equipment rental and leasing”
is used.

6. Data describing provincial approaches to innovation were drawn from the Survey of Innovation,
2003 (Statistics Canada, 2003). The survey “is based on the Oslo Manual (OECD/Eurostat, 1997)
which outlines proposed guidelines for collecting and interpreting innovation data at the level of
the firm” (Ibid.). Its population includes those establishments with more than 15 employees and
over $250,000 per year in revenues. Four broad industry classifications were sampled, including
the ICT service industry defined in Table 1. The results are at the provincial aggregation.
Procedure
The effect of an innovative culture on regional economic performance is not direct. The literature
suggests a causal relationship similar to that outlined in Figure 1Error! Reference source not
found.. A high level of innovation is predicted for regions where industry approaches innovation
in a collaborative manner. Conversely, a secretive approach that relies on strict intellectual
property protection, and is generates large vertically integrated companies, should result in a
lower level of regional innovation. In turn, endogenous growth theory predicts that the level of
innovation will influence a region‟s economic growth.
Figure 1: Predicted Pattern of Causation for Innovation and Economic Performance
Predicted Pattern of Causation for
Innovation and Economic Performance
Protean
(Collaborative Learning
and Relationships)
Product and
Culture/Attitudes Economic
Process
Toward Innovation Performance
Innovations
Autarkic
(Strict IP Protection
and Acquisition)
A number of variables represent the culture/attitudes toward innovation among Canada‟s
provinces. Each variable represents the proportion of firms which recognize the importance of, or
are actively engaged in, a given innovation strategy. Summary statistics for these variables are
included in Table 2.

7. Table 2: Variables defining a province’s culture/attitudes toward innovation
Variable Mean SD
Proximity to knowledge institutions is highly or moderately highly
14.24 6.40
important to success (ProxKnow).
Proximity to knowledge institutions is moderately highly important to
11.11 4.14
success (ProxKnowMod).
Proximity to knowledge institutions is highly important to success
3.13 2.72
(ProxKnowHigh).
Involvement in industry associations is highly or moderately highly
25.00 9.62
important to success (IndAssoc).
Involvement in industry associations is moderately highly important to
18.60 9.76
success (IndAssocMod).
Involvement in industry associations is highly important to success
6.40 3.24
(IndAssoc High).
The use of partnerships, strategic alliances or joint ventures to acquire
42.61 18.81
knowledge is highly or moderately highly important to success (Partner).
The use of partnerships, strategic alliances or joint ventures to acquire
29.65 6.36
knowledge is moderately highly important to success (PartnerMod).
The use of partnerships, strategic alliances or joint ventures to acquire
18.29 8.26
knowledge is highly important to success (Partner High).
Collaborated and cooperated to develop new innovations (CollabTOT). 59.40 10.20
Collaborated with competitors to innovate (CollabCOMP). 29.66 8.54
Collaborated with universities or other higher education institutes to
22.64 10.15
innovate (CollabUNIV).
Used patents to protect intellectual property (Patents). 15.28 3.60
Used secrecy to protect intellectual property (Secrecy). 50.74 8.91
Used a lead-time strategy to protect intellectual property (LeadTime). 53.09 10.80
An additional variable representing the average firm size for each province was created by
dividing the total ICT employment in each province by the population of ICT firms identified in
the documentation for the Survey of Innovation (Statistics Canada, 2003). The mean firm size is
52 full-time equivalents (FTEs) with a standard deviation of 15 FTEs.
Simple correlation was used to test the relationships in the model. For the first set of relationships
(where the approach to innovation is said to influence the level of innovation), the variables
identified above were tested against the proportion of innovative ICT firms in each province4.
Pearson‟s product moment correlation coefficient (r) was calculated. Each r-value was interpreted
using a standard rubric (see Table 3).
4
The variable for “Percentage of innovative business units in Canada during the period 2001 to 2003”
(Innovators) has a mean of 74.67 and a standard deviation of 7.83.

8. Table 3: Pearson’s Product Moment Correlation Coefficient Interpretation
Association Absolute r-value
Perfect (P) 1.00
Strong (S) 0.75 – 0.99
Moderately Strong (M) 0.50 – 0.74
Weak (W) 0.01 – 0.49
None (N) 0.00
A measure of relative regional economic performance was calculated to test the second half of the
model. The three elements of „shift and share‟ (see Newkirk, 2002) were calculated for the ICT
industry in each province for the period January 2001 – January 2011. This is a statisitical
accounting framework widely used for regional economic analysis. It yields a „differential shift
coefficient‟, which is a standardized comparable measure of regional performance. This the
context of this study, it represents the quality of regional economic performance in the ICT
industry separate from the influences of national economic growth and national industry growth
(decline). The full results of the shift and share analysis can be found in Appendix A. Differential
shift coefficients for each province were tested for correlation with the proportion of innovative
ICT firms in each province.
Limitations
Two key limitations to this method are acknowledged. First, there is broad recognition of the
inherent time lag in the innovation model. Feldman and Florida (1994, p. 217) note that it is
difficult to measure the length of this time lag. However, Mansfield (1991) suggests the lag is in
the order of 7 years (with a standard deviation of 2 years) between an academic research finding
and commercial introduction of a new product. The method presented above attempts to
compensate by comparing innovation data at the beginning of a time period (2001-2003) with
economic data for the subsequent decade (2001-2011).
The second limitation is in using a provincial level of analysis. As Feldman and Florida (1994, p.
216) explain, in the American context, “using the state as the unit of analysis inevitably obscures
spatial processes that occur within a state or across state boundaries.” Unfortunately, results from
the Survey of Innovation (or any similar data) are not available at a sub-provincial level.
An additional two limitations were addressed in the data analysis. First, most of the Survey of
Innovation results from Prince Edward Island have been suppressed under Statistics Canada‟s
privacy policies. Unfortunately this meant that PEI could not be included in this study. In other
provinces, data for certain sub-industries were suppressed for one of the two time periods. In
these cases, the sub-industries were not included in provincial industry employment totals.
Furthermore, the ICT industry classification identified above included wired telecommunication
companies. In many Canadian provinces, only one firm (the current or former crown telephone

9. corporation) fits this category. In those cases where more than one firm is found in the category,
the majority of the labour force is still employed by the one dominant firm. This means that for
many provinces employment data in the 5171 NAICS category has been suppressed. This NAICS
category has therefore been completely excluded from this study‟s ICT industry definition.
Results
Innovation Across Canada
The results indicate a high level of innovation among ICT firms across the country. New
Brunswick had the greatest proportion of innovators (83.1%), followed by British Columbia
(81.1%). Saskatchewan had the lowest proportion of innovators (60.6%), followed by
Newfoundland and Labrador (63.5%). The other provinces had innovation rates ranging from 72-
79% (see Figure 2). These findings support Bourgeois and LeBlanc‟s (2002) conclusion that
firms in Atlantic Canada innovate at, or above, the national level. Innovation in Canada‟s ICT
industry does not seem to follow typical lines of regional disparity. However, regional differences
in innovativeness are still evident and deserve closer examination.
Figure 2: Proportion of Innovative ICT Firms by Province
Proportion of Innovative ICT Firms
by Province (2001-2003)
63.5
81.1
74.8 60.6 72.7
77.5
79.5
79.2
83.1
Proportion of Innovative ICT Firms
50% 100%

10. Approach to Innovation vs. Innovativeness
Canada‟s highest levels of collaboration were found in the east (see Figure 3). Although
Newfoundland and Labrador had the second lowest level of innovation, it had by far the highest
level of collaboration. If these findings held tightly to the literature, Newfoundland and
Labrador‟s collaborative environment would have led to a high level of innovation. There may
however be additional obstacles in that province. Further research should be conducted to identify
barriers to innovation in the poorer provinces. The literature suggests that these barriers might
include a lack of venture capital. Additional research can also explore any functional differences
in collaboration across the country.
Figure 3: Proportion of Collaborative ICT Firms by Province (2001-2003)
Proportion of Collaborative ICT Firms
by Province (2001-2003)
83.3
52.6
51.0 57.6 52.2
60.6
53.1
66.2
58.0
Proportion of Collaborative ICT Firms
50% 100%
Some evidence did emerge to support the link between approaches to innovation and regional
innovativeness. Unfortunately many of the innovation variables were only weakly associated with
the level of innovation (see Table 4). Six variables did yield a moderately strong association.
Surprisingly, a negative relationship was found for both the importance placed on industry
associations (IndAssoc) and proximity to knowledge institutions (ProxKnow). This suggests that
innovation is lower where firms identified these success factors as highly and moderately
important. Perhaps these firms are not actually engaged in these collaborations but simply see
them as important. This logic is supported by additional findings. First, innovation was greater
where firms noted the importance of partnerships, strategic alliances and joint ventures (Partner).
Also, a moderately strong positive relationship was found between two measures of collaborative
action and the level of innovativeness. The most innovative provinces saw higher levels of
collaboration with competitors (CollabCOMP) and with universities (CollabUNIV). These
findings all point to the relationship between collaboration and innovation. No strong evidence
emerged to support or refute the proposition that secrecy strategies undermine regional levels of
innovation.

11. Table 4: Correlation of Innovation Strategies with Innovators
Variable r-value Variable r-value
ProxKnow -0.55 Partner High +0.05
ProxKnow Mod -0.43 CollabTOT -0.44
ProxKnow High -0.65 CollabCOMP +0.56
IndAssoc -0.40 CollabUNIV +0.65
IndAssoc Mod -0.53 Patents -0.44
IndAssoc High +0.39 Secrecy +0.22
Partner +0.58 LeadTime +0.45
Partner Mod -0.03 AvgFirmSize +0.71
Another surprising finding was that firm size has a moderately strong positive association with
innovativeness. The literature predicts that autarky will be present in regions where average firm
size is large. This may not be the case for the Canadian ICT industry since the provincial average
firm sizes are all below 75 FTEs. The mean firm size is only 52 FTEs and there is little
interprovincial variation (a standard deviation of only 15 FTEs). There simply is not the same
contrast in average firm size among Canadian provinces as the contrast Saxenian (1998) saw
between Route 128 and Silicon Valley. There appears to be a „small business bias‟ in the
Canadian ICT sector (when the large telephone companies are excluded). The positive correlation
may also indicate the relative strength or maturity of larger SMEs.
Innovativeness vs. Economic Performance
Between 2001 and 2011, employment in the ICT service industry declined in every province
except New Brunswick, Quebec, Alberta and British Columbia. The „shift and share‟ results
indicate that each province should have seen 13% employment growth thanks to the national
employment trend. However, employment in the ICT industry underperformed with respect to the
national economy. Nationally the change in ICT sector employment was a net increase of only
6% (or 21,307 FTEs). As a result, the industry mix coefficient is set to -7% to indicate that the
ICT industry‟s performance offset the overall performance of the national economy. In addition
to poor national performance, the industry performed poorly regionally. New Brunswick, Quebec,
Alberta and British Columbia saw positive differential shifts. But all other provinces saw negative
differential shifts (see Figure 4). The provinces with the lowest differential shifts are located in
the east (Nova Scotia and Newfoundland and Labrador). But there were also low shifts in Ontario
and Manitoba. Again, this pattern does not follow the predicted lines of regional disparity.

12. Figure 4: Differential Shift for ICT Industries by Province (2001-2011)
Differential Shift for ICT Industries
by Province (2001-2011)
-0.30
+0.05
+0.09 -0.20 -0.26
+0.08
-0.07
-0.33
+0.08
Differential Shift Coefficient
-0.35 +0.35
The evidence linking innovation to regional economic performance is moderately strong. The
relationship between the proportion of innovators (Innovators) and differential shift (DiffShift) is
positive, and moderately strong (r = 0.54). It is possible that the relationship could be stronger, if
not for other barriers preventing the translation of innovations into commercially viable products
and services.
It is useful to note the results from a direct test of association between the innovation approach
variables and the differential shift. Although there is clearly an intermediary step in the
innovation process, some interesting findings emerged. First, the relationship of firm-university
collaboration to the differential shift is stronger (r = 0.93) than its relationship to the level of
innovation (r = 0.65). The former relationship was the strongest identified in this study. It
suggests that firms may not be only collaborating with universities to develop innovations. They
may also be commercializing innovations already developed by university researchers.
A second interesting finding, is that perhaps not all collaborations are created equally. Provinces
with high levels of total collaboration (CollabTOT) generally had lower differential shift
coefficients (r = -0.54). It is possible that some types of formalized collaboration are more likely
to result in the kind of vertically integrated systems Saxenian described along Route 128. Closer
examination is required.
Finally, some evidence emerged to support the theory that wide-spread patent protection
strategies could hinder economic performance. The relationship of patent-use to regional
differential shifts was negative and moderately strong (r = -0.54). The literature suggested that
patent-use can be indicative of an autarkic industrial culture, and that such autarky can stifle
economic performance.

13. Conclusions
The correlation results support the structure of the causal model being tested (see Figure 5).
Provinces with higher levels of open collaboration with universities saw a correspondingly high
proportion of their ICT firms innovating, and correspondingly stronger economic performance.
Provinces with higher levels of patent use saw lower levels of innovation and poorer regional
economic performance. Furthermore, the evidence connecting levels of innovation with economic
performance was moderately strong. Clearly, innovation was connected to economic performance
in the ICT industry between 2001 and 2011. However, the approach to innovation (protean versus
autarkic) was critical.
Figure 5: Observed Pattern of Causation for Innovation and Economic Performance
Observed Pattern of Causation for
Innovation and Economic Performance
Protean
r = 0.93
(Collaborative Learning (CollabUNIV)
and Relationships) r = 0.65
(CollabUNIV)
Regional
Culture/Attitudes Innovators
Advantage
Toward Innovation (Innovators)
r = 0.54 (DiffShift)
(Patents)
Autarkic r = -0.44
(Patents)
(Strict IP Protection r = -0.54
and Acquisition)
The findings presented here support the idea that regional approaches to innovation can affect
regional economic growth. Variation was found among Canada‟s provinces in terms of their
innovation cultures, their level of innovation activity, and their relative employment
growth/decline. The most successful provinces were home to a greater proportion of firms that
collaborate with universities. However, not all other forms of collaboration seem to yield positive
results (more research is needed). The least successful provinces were home to a greater
proportion of highly secretive firms that used patents to protect their intellectual property.
These findings support the conclusion that provinces with more protean industrial cultures
outperform provinces with more autarkic industrial cultures. A culture of open innovation can
boost innovativeness, creating a regional economic advantage. Business schools can therefore
contribute to regional advantage by furthering research on inter-firm collaboration, and by
working with industry to create product, process, and organizational innovations.

14. APPENDIX A: Shift and Share Coefficients
Employment in 2001
Canada NL PE NS NB PQ ON MB SK AB BC
ICT 387,916 1,465 288 6,069 3,300 82,765 185,822 6,248 1,679 32,276 37,315
Total 12,482,719 159,254 52,577 350,108 278,587 2,939,945 4,919,896 493,259 364,316 1,315,062 1,567,213
Employment in 2011
Canada NL PE NS NB PQ ON MB SK AB BC
ICT 374,723 1,114 480 4,379 3,772 88,963 177,954 5,366 3,182 36,125 39,630
Total 14,524,398 190,620 59,592 396,748 307,520 3,306,709 5,603,240 550,760 441,651 1,739,056 1,872,590
Change 2001-2011
Canada NL PE NS NB PQ ON MB SK AB BC
ICT -3% -24% 67% -28% 14% 7% -4% -14% 90% 12% 6%
Total 13% 9% 6% 8% 3% 8% 12% 11% 19% 29% 17%
Shift and Share Coefficients
NL PE NS NB PQ ON MB SK AB BC
Regional Share 0.13 0.13 0.13 0.13 0.13 0.13 0.13 0.13 0.13 0.13
Industry Mix -0.17 -0.17 -0.17 -0.17 -0.17 -0.17 -0.17 -0.17 -0.17 -0.17
Differential Shift -0.21 0.70 -0.24 0.18 0.11 -0.01 -0.11 0.93 0.15 0.10
Shift and Share Components - Analysis of Change 2001-2011
NL PE NS NB PQ ON MB SK AB BC
2001 Employment 1,465 288 6,069 3,300 82,765 185,822 6,248 1,679 32,276 37,315
Regional Share 193 38 800 435 10,916 24,508 824 221 4,257 4,922
Industry Mix (243) (48) (1,007) (547) (13,731) (30,828) (1,037) (279) (5,355) (6,191)
Differential Shift (301) 202 (1,484) 584 9,013 (1,548) (670) 1,560 4,947 3,584
2011 Employment 1,114 480 4,379 3,772 88,963 177,954 5,366 3,182 36,125 39,630

15. APPENDIX B: Correlation Tables
Effect of Innovation Variables on the Differential Shift for ICT Industry in each Province
Mean StDev r
Differential Shift (0.09) 0.18
ProxKnow 14.24 6.40 -0.48
ProxKnow Mod 11.11 4.14 -0.45
ProxKnow High 3.13 2.72 -0.46
IndAssoc 25.00 9.62 -0.45
IndAssoc Mod 18.60 9.76 -0.38
IndAssoc High 6.40 3.24 -0.21
Partner 42.61 18.81 -0.10
Partner Mod 29.65 6.36 -0.06
Partner High 18.29 8.26 -0.65
Innovators 74.67 7.83 0.54
CollabTOT 59.40 10.20 -0.54
CollabCOMP 29.66 8.54 0.23
CollabUNIV 22.64 10.15 0.93
Patents 15.28 3.60 -0.54
Secrecy 50.74 8.91 0.22
LeadTime 53.09 10.80 0.43
AvgFirmSize 52.48 15.28 0.62
Effect of Approaches to Innovation on the Level of Innovation in Each Province
Mean StDev r
Innovators 74.67 7.83
ProxKnow 14.24 6.40 -0.55
ProxKnow Mod 11.11 4.14 -0.43
ProxKnow High 3.13 2.72 -0.65
IndAssoc 25.00 9.62 -0.40
IndAssoc Mod 18.60 9.76 -0.53
IndAssoc High 6.40 3.24 0.39
Partner 42.61 18.81 0.58
Partner Mod 29.65 6.36 -0.03
Partner High 18.29 8.26 0.05
CollabTOT 59.40 10.20 -0.44
CollabCOMP 29.66 8.54 0.56
CollabUNIV 22.64 10.15 0.65
Patents 15.28 3.60 -0.44
Secrecy 50.74 8.91 0.22
LeadTime 53.09 10.80 0.45
AvgFirmSize 52.48 15.28 0.71

16. References
Acs, Z. and Varga, A., “Geography, Endogenous Growth and Innovation,” International Regional
Science Review, 25 (1), (2002), 132-148.
Beaudin, M. and S. Breau, Employment, Skills, and the Knowledge Economy in Atlantic Canada,
Maritime Series, Monographs, Moncton, NB: The Canadian Institute for Research on Regional
Development, 2001.
Betts, Y., “II. Resources and Technology: The Implications of Technological Change for Human
Resource Policy,” Canada in the 21st Century. Ottawa, ON: Industry Canada Research
Publications Program, 1998.
Bourgeois, Y. and S. LeBlanc, Innovation in Atlantic Canada, Maritime Series, Monographs.
Moncton, NB, The Canadian Institute for Research on Regional Development, 2002.
Feldman, M.P. and R. Florida, “The Geographic Sources of Innovation: Technological
Infrastructure and Product Innovation in the United States,” Annals of the Association of
American Geographers, 84 (2), (1994), 210 – 229.
Hall, P., “The New Geography of Innovation,” in C. Bryant (ed.) Waterloo Lectures in
Geography, Waterloo: Department of Geography, University of Waterloo, 1, (1984), 29 – 38.
Mansfield, E.J., “Academic Research and Industrial Innovation,” Research Policy, 20, (1991), 1 –
12.
Maskell, P. and A. Malmberg, “The Competitiveness of Firms and Regions: „Ubiquitification‟
and Localized Learning,” European Urban and Regional Studies, 6 (1), (1999), 9 – 25.
Morgan, K., “The Learning Region: Institutions, Innovation and Regional Renewal,” Regional
Studies, 31 (5), (1997), 491 – 503.
Nelson, R.,“The Sources of Industrial Leadership: A Perspective on Industrial Policy,” De
Economist, 147, (1999), 1 – 18.
Nelson, R. (Ed.), National Innovation Systems, Oxford, UK: Oxford University Press, 1993.
Newkirk, R., Techniques for Regional Planning. Waterloo, ON: University of Waterloo under
license from ingenious solutions inc., 2002.
OECD/Eurostat, Proposed Guidelines for Collecting and Interpreting Innovation Data (Oslo
Manual), Paris: Author, 1997.
Saxenian, A., Regional Advantage: Culture and Competition in Silicon Valley and Route 128.
Cambridge, MA: Harvard University Press, 1994.

17. Saxenian, A., “A Climate for Entrepreneurship. Presentation at Creating an Environment for
Growth,” Proceedings of the XII International Conference of Private Business Associations,
Stockholm, Sweden, (June 1998).
Schumpeter, J., Capitalist, Socialism and Democracy. London: Allen & Unwin, 1943.
Statistics Canada, Survey of Innovation 2003 [machine readable data file and documentation],
Ottawa: Statistics Canada, Catalogue no. 88-524-XCB2005001, (2003).
Statistics Canada, Survey of Employment, Earnings and Hours [machine readable data file and
documentation], Ottawa: Statistics Canada, Catalogue no. 72-002-XIB (CANSIM Table 281-
0023), (2004).
Storper, M., “The Limits to Globalization: Technology Districts and International Trade,”
Economic Geography, 68, (1992), 60 – 93.
Storper, M., “Institutions of the learning economy.” Proceedings of the Conference on
Employment and Growth in the Knowledge-based Economy, Copenhagen, Denmark, (November,
1994).
Storper, M., “The resurgence of regional economic ten years later: the region as a nexus of
untraded interdependencies,” European Urban and Regional Studies, 2, (1995), 191 – 221.